Titlebook: Explainable AI Recipes; Implement Solutions Pradeepta Mishra Book 2023 Pradeepta Mishra 2023 Explainable AI.Python.Artificial Intelligence

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Explainability for Nonlinear Supervised Models, in the case of classification, the output variable is binary or multinomial. A binary output variable has two outcomes, such as true and false, accept and reject, yes and no, etc. In the case of a multinomial output variable, the outcome can be more than two, such as high, medium, and low. In this

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Explainability for Ensemble Supervised Models,ions are aggregated in ensemble models to generate the final models. In the case of supervised regression models, many models are generated, and the averages of all the predictions are taken into consideration to generate the final prediction. Similarly, for supervised classification problems, multi

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Explainability for Natural Language Processing,ELI5. The objective of explaining the text classification tasks or sentiment analysis tasks is to let the user know how a decision was made. The predictions are generated using a supervised learning model for unstructured text data. The input is a text sentence or many sentences or phrases, and we t

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